Bottom Line:
Here, we present a mathematical modeling framework for antisense transcription that combines the effects of both transcriptional interference and cis-antisense regulation.We identify important parameters affecting the cellular switch response in order to provide the design principles for tunable gene expression using antisense transcription.This presents an important insight into functional role of antisense transcription and its importance towards design of synthetic biological switches.

Affiliation: Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, United States of America.

ABSTRACTAntisense transcription has been extensively recognized as a regulatory mechanism for gene expression across all kingdoms of life. Despite the broad importance and extensive experimental determination of cis-antisense transcription, relatively little is known about its role in controlling cellular switching responses. Growing evidence suggests the presence of non-coding cis-antisense RNAs that regulate gene expression via antisense interaction. Recent studies also indicate the role of transcriptional interference in regulating expression of neighboring genes due to traffic of RNA polymerases from adjacent promoter regions. Previous models investigate these mechanisms independently, however, little is understood about how cells utilize coupling of these mechanisms in advantageous ways that could also be used to design novel synthetic genetic devices. Here, we present a mathematical modeling framework for antisense transcription that combines the effects of both transcriptional interference and cis-antisense regulation. We demonstrate the tunability of transcriptional interference through various parameters, and that coupling of transcriptional interference with cis-antisense RNA interaction gives rise to hypersensitive switches in expression of both antisense genes. When implementing additional positive and negative feed-back loops from proteins encoded by these genes, the system response acquires a bistable behavior. Our model shows that combining these multiple-levels of regulation allows fine-tuning of system parameters to give rise to a highly tunable output, ranging from a simple-first order response to biologically complex higher-order response such as tunable bistable switch. We identify important parameters affecting the cellular switch response in order to provide the design principles for tunable gene expression using antisense transcription. This presents an important insight into functional role of antisense transcription and its importance towards design of synthetic biological switches.

pone.0133873.g002: Algorithm for discrete TI model.(A) A pair of convergent promoters pX (present on sense/top DNA strand) and pY (present on antisense/bottom DNA strand) separated by overlapping DNA of length L is shown. Promoters pX and pY drive expression of genes X and Y respectively, which produce full-length transcripts x and y (denoted by bold arrows) respectively. For each ith and jth round of transcription from pX and pY promoters respectively, RNAP (denoted by large grey ovals) form DNA-bound RNAP complexes at the respective promoter region following a binding (τBX and τBY) and initiation (τIX and τIY) process. After firing, the center of RNAP moves to first position of the overlapping region to form an elongation complex (EC, denoted by smaller grey ovals). The time taken for each ith EC (fired from pX) to reach kth position on sense strand (tX,i,k) as well as the time taken for each jth EC (fired from pY) to reach hth position on the antisense (tY,j,h) strand along the overlapping DNA are tracked. The footprint of an EC is denoted by fp. (B) For each ith and jth rounds of transcription, the model calculates the outcome of TI depending on the region where opposing RNAPs meet. Occlusion and sitting duck interference occur at the promoters pX (left panels) or pY (right panels), and RNAP collisions between ECs occur along the overlapping DNA (middle panel) following the mathematical constraints shown. Upon RNAP collision, one or both ECs on the sense and antisense strand fall off the DNA and result in production of truncated transcripts xk and yh (denoted by dashed arrows) from pX and pY respectively. In absence of any kind of TI, transcription is successful, producing a full-length transcript (x, y). Once 30,000 rounds of transcription from the stronger promoter have been calculated the net rate of production of full-length (kx and ky) and truncated RNA ( and ) are obtained.

Mentions:
We developed a discrete model that simulates RNAP traffic originating from a general set of two convergent, non-overlapping promoters pX and pY present on sense and antisense strands of DNA, driving the expression of genes X and Y, respectively. The model calculates the outcome of every single round of transcription by tracking binding and movement of RNAP along three different regions along the DNA: the pX promoter region from position -70 to -1, the intermediate overlapping region of length L, which spans between positions +1 and L, and promoter pY region from position L+1 to L+70 (Fig 2).

pone.0133873.g002: Algorithm for discrete TI model.(A) A pair of convergent promoters pX (present on sense/top DNA strand) and pY (present on antisense/bottom DNA strand) separated by overlapping DNA of length L is shown. Promoters pX and pY drive expression of genes X and Y respectively, which produce full-length transcripts x and y (denoted by bold arrows) respectively. For each ith and jth round of transcription from pX and pY promoters respectively, RNAP (denoted by large grey ovals) form DNA-bound RNAP complexes at the respective promoter region following a binding (τBX and τBY) and initiation (τIX and τIY) process. After firing, the center of RNAP moves to first position of the overlapping region to form an elongation complex (EC, denoted by smaller grey ovals). The time taken for each ith EC (fired from pX) to reach kth position on sense strand (tX,i,k) as well as the time taken for each jth EC (fired from pY) to reach hth position on the antisense (tY,j,h) strand along the overlapping DNA are tracked. The footprint of an EC is denoted by fp. (B) For each ith and jth rounds of transcription, the model calculates the outcome of TI depending on the region where opposing RNAPs meet. Occlusion and sitting duck interference occur at the promoters pX (left panels) or pY (right panels), and RNAP collisions between ECs occur along the overlapping DNA (middle panel) following the mathematical constraints shown. Upon RNAP collision, one or both ECs on the sense and antisense strand fall off the DNA and result in production of truncated transcripts xk and yh (denoted by dashed arrows) from pX and pY respectively. In absence of any kind of TI, transcription is successful, producing a full-length transcript (x, y). Once 30,000 rounds of transcription from the stronger promoter have been calculated the net rate of production of full-length (kx and ky) and truncated RNA ( and ) are obtained.

Mentions:
We developed a discrete model that simulates RNAP traffic originating from a general set of two convergent, non-overlapping promoters pX and pY present on sense and antisense strands of DNA, driving the expression of genes X and Y, respectively. The model calculates the outcome of every single round of transcription by tracking binding and movement of RNAP along three different regions along the DNA: the pX promoter region from position -70 to -1, the intermediate overlapping region of length L, which spans between positions +1 and L, and promoter pY region from position L+1 to L+70 (Fig 2).

Bottom Line:
Here, we present a mathematical modeling framework for antisense transcription that combines the effects of both transcriptional interference and cis-antisense regulation.We identify important parameters affecting the cellular switch response in order to provide the design principles for tunable gene expression using antisense transcription.This presents an important insight into functional role of antisense transcription and its importance towards design of synthetic biological switches.

Affiliation:
Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, United States of America.

ABSTRACTAntisense transcription has been extensively recognized as a regulatory mechanism for gene expression across all kingdoms of life. Despite the broad importance and extensive experimental determination of cis-antisense transcription, relatively little is known about its role in controlling cellular switching responses. Growing evidence suggests the presence of non-coding cis-antisense RNAs that regulate gene expression via antisense interaction. Recent studies also indicate the role of transcriptional interference in regulating expression of neighboring genes due to traffic of RNA polymerases from adjacent promoter regions. Previous models investigate these mechanisms independently, however, little is understood about how cells utilize coupling of these mechanisms in advantageous ways that could also be used to design novel synthetic genetic devices. Here, we present a mathematical modeling framework for antisense transcription that combines the effects of both transcriptional interference and cis-antisense regulation. We demonstrate the tunability of transcriptional interference through various parameters, and that coupling of transcriptional interference with cis-antisense RNA interaction gives rise to hypersensitive switches in expression of both antisense genes. When implementing additional positive and negative feed-back loops from proteins encoded by these genes, the system response acquires a bistable behavior. Our model shows that combining these multiple-levels of regulation allows fine-tuning of system parameters to give rise to a highly tunable output, ranging from a simple-first order response to biologically complex higher-order response such as tunable bistable switch. We identify important parameters affecting the cellular switch response in order to provide the design principles for tunable gene expression using antisense transcription. This presents an important insight into functional role of antisense transcription and its importance towards design of synthetic biological switches.